Compressed sensing in hyperpolarized 3He Lung MRI

In this work, the application of compressed sensing techniques to the acquisition and reconstruction of hyperpolarized ³He lung MR images was investigated. The sparsity of ³He lung images in the wavelet domain was investigated through simulations based on fully sampled Cartesian two‐dimensional and three‐dimensional ³He lung ventilation images, and the k‐spaces of 2D and 3D images were undersampled randomly and reconstructed by minimizing the L1 norm. The simulation results show that temporal resolution can be readily improved by a factor of 2 for two‐dimensional and 4 to 5 for three‐dimensional ventilation imaging with ³He with the levels of signal to noise ratio (SNR) (～19) typically obtained. The feasibility of producing accurate functional apparent diffusion coefficient (ADC) maps from undersampled data acquired with fewer radiofrequency pulses was also demonstrated, with the preservation of quantitative information (mean ADC_cs ～ mean ADC_full ～ 0.16 cm² sec^?1). Prospective acquisition of 2‐fold undersampled two‐dimensional ³He images with a compressed sensing k‐space pattern was then demonstrated in a healthy volunteer, and the results were compared to the equivalent fully sampled images (SNR_cs = 34, SNR_full = 19). Magn Reson Med 63:1059–1069, 2010. © 2010 Wiley‐Liss, Inc.